. Rebecca A. Zulli, Cynosure Consulting c American Society for Engineering Education, 2019 AN ASSET APPROACH TO BROADENING P A R T I C I P AT I O N TIP S A ND T OOLS FOR STRATEGIC P L A NNINGA D R I E N N E S M I T H & R E B E C C A Z U L L I L OW EINTRODUCTION• All too often when thinking about recruiting, supporting, and retaining diverse students in our STEM majors and programs, the situation is approached from a deficit mindset; that is, one that focuses on what students or environments lack that must be remedied.• In our work supporting STEM departments with their broadening participation efforts, we focus on fostering an asset-minded approach to strategic planning.• This approach is grounded
]: ( s f ) D 2 18v s Specific Weight of the Sphere D Diameter of Sphere f Specific Weight of the Fluid v Velocity of the SphereAt this stage, the instructor has the freedom to custom design the animation for a variety ofdifferent question presentations. Table 2 shows possible computational questions for a singlefluid. Once students compute any of the following scenarios, additional questions can beprovided on asking them to rank the fluids by their viscosities, specific weights or speeds, whichprovide a chance for students to review the animation and compare different fluids. Table 2. Layout of possible
Session 1793 NASA KC-135A Reduced Gravity Undergraduate Program G. K. Watkins, K.L. Locklear, R. J. Goins, C.W. Spivey William States Lee College of Engineering The University of North Carolina at Charlotte Charlotte, NC 28223AbstractThe Johnson Space Center of the National Aeronautics and Space Administration(NASA) sponsors the Reduced Gravity Student Flight Opportunities Program. Thehighly competitive program affords undergraduate students the opportunity to propose,design, fabricate, execute, and evaluate reduced gravity experiments. NASA s KC-135Aresearch
synthesizing thedata can be assigned to an interested individual(s) in the department or college, a so-called qualitychampion.Although the first three components lead to the guiding principles, it is critical that the facultyagree on those principles before beginning the assessment. This will ensure that the correctmeasurement mechanisms are in place (Dierick and Dochy, 2001; Wolf and Cumming, 2000). Inaddition, faculty agreement on the guiding principles defines the culture, that is the norms ofexpected behavior, for departmental assessment. Faculty buy-in to the guiding principles is anecessary aspect of the structure to prevent backlash from the inevitable change-managementsyndrome. Well-defined principles also set boundaries that the faculty can
7.5 th turn = 659.73 in. Right s ens or location 22.5 th turn = 1979.20 in. Right end of coil 23.5 turns = 2067.17 in. (all d istances measured from left end of coil) Distance between Left end and left sens or = 659.73 in Left sens or and right s ens or = 1319.47 in. Right sens or and right end
(11) dt Lr Lr did Lr R s M 2 Rr MRr ( )id eiq d 2 2 dt Lr Ls M ( Lr Ls M ) Lr ( Lr Ls M 2 ) Lr M Lr q ud (12
Session 1664 THE BEST OF BOTH WORLDS: A NEW LOOK AT COOPERATIVE EDUCATION Charles P. Wentz, Rudy Wojtecki Kent State University Trumbull CampusIntroduction $Probably no social partnership holds more potential for both immediate and long-term impact on America s future . . . than the budding cooperation between schools and some businesses . . . #1 $Norman Augustine, Chairman and CEO of Martin Marietta Corporation, !suggested that with the end of the Cold War, engineering education needed a new set of guiding principles and that !engineers now
withoutgraduate degrees. In multiple instances, employers and/or graduate school representatives haveexpressed how impressive and important the undergraduate research experience was, not only inthe initial hiring and financial support decisions, but also in the rate and quality with which the Page 15.939.2new hires performed their responsibilities. The success of these students has been a majorcomponent of the author‟s positive reputation in this research arena.The author has made a strong effort to integrate undergraduate research in semiconductor andthin film materials with instruction. For example, he developed two lecture/laboratory coursepairs in
and has redesigned the course to include a variety of sustainability and climate change(S/CC) topics situated within the context of social entrepreneurship and wicked problems (WPs).Since 2015, the author has been periodically modifying and improving the course. This paperdescribes the redesign and implementation of this course since 2015, focusing on the sectiontaught in 2023, as the most recent iteration of the course.The course focuses on three overarching topics: 1. Wicked problems (WPs). WPs are defined as very complex problems. They are hard to define and are characterized by having no stopping point, no point in which the problem has been clearly “solved” [1]. Climate change has been described as an example of a WP [2
. It'snecessary in phase diagrams to prevent clutter and confusion, but students can benefit by seeingdatapoints on S/N fatigue curves and in graphs of Charpy impact energy vs. temperature. In suchgraphs, data points help students understand the degree of scatter that is normally found in thesemechanical tests.Some limitations of graphing software can be overcome by changing default settings on fonts,standard symbols, line thicknesses, hard-to-read vertically-oriented text, or a legend that fails tolist symbols in the same order as they appear on the graph. Other limitations are best overcomeby converting a graph to artwork.This paper demonstrates ways to improve the quality of engineering graphs used in materialseducation by comparing many examples of
range of industrial experience for these individuals was 2–43 years. Seventy five percent of (or six of the eight) participants indicated that they had atleast 15 years of relevant STEM industry experience. The gender distribution of industryprofessionals who participated in the interviews were 5 males and 3 females. The 15student participants included a spread of both underclassmen and upperclassmen. Theage range of student participants in the qualitative interviews was 18–24 years and thegender distribution of these students was 8 males and 7 females. The skills identified duringthe qualitative interviews weregrouped into a list of STEM Skill Indicators that were linked with the following classified STEMSkill Factors: Soft skills (S
design, this would be analogous to a team generatinghypotheses for a solution to a challenge (in any given form), stating: what the solution/artifactconsists of; who is the end user(s); what problem is solved for them; how will a solution bedelivered; what other competing solutions exist for a given problem; how will end users learn(and why they will want a solution); and, for a solution that is part of an existing category, if itmodifies such a category, or if it creates a new category. In contrast, the guide to growthapproach [54] suggests that opportunities should come from pattern recognition activities, aswell as awareness of the characteristics of a desired end goal. Emphasis is placed on problemsthat potential end-users cannot adequately
software program developed by S. Klein and W. Beckman from the University ofWisconsin-Madison. EES is an acronym for Engineering Equation Solver and has been selectedin this study to discuss the benefits of incorporating computer software for teaching introductoryareas of physics. The EES program was chosen because it is intuitive and simple to use, and hasbeen developed with features of noticeable relevance to engineering training.EES is an equation solver with built-in functions for thermophysical properties. With EES,therefore, it is no longer necessary to use tabulated information from texts or handbooks in a widevariety of physics problems. In general, EES can be used to solve algebraic, differential andintegral equations, check unit
response rates and N were as follows: Fellow N=8, Response Rate=100% (8/8); ResearchAdvisors N-7, Response Rate=78% (7/9); Participating Teachers N=8, Response Rate=100%(8/8). One of the fellows has two advisors. Surveys were sent as an attachment to an email letterrequesting participation. Quantitative responses were indicated by the responder underlining or Page 15.667.4making bold their choice. Tabulation and data analysis were carried out by the evaluator withinput from the PI.Quantitative FindingsThe responses to fellows, advisors and teachers to the target themes in the surveys are shownbelow. Key: GX= to a great extent; S= somewhat; N= not at
thickness). They quantifiedcharring using an automated pixel counting method adapted from work on air void detection inconcrete [9]. The control factors responsible for the specimens in Figure 1’s Row A exhibitedthe most charring and highest variation as measured by signal to noise ratio (S/N). Row Bexhibited the least.For the individual projects one student chose to investigate laser settings that minimizeengraving time. Another student explored the effects on the surface quality of parts printed withthe Stratasys F170. He measured differences in surface height to ±0.0005 in to quantify surfacequality. This student went beyond the means and signal-to-noise (S/N) ratios required in TMdata analysis, conducting a one-factor ANOVA using R-Studio
employing only two-stages, the design of amplifier is already complex, in that achievingperfect inter-stage matching becomes difficult thereby causing device failure as return losses are small. Toresolve this, the design of amplifier first stage is undertaken independently, and then the second stage iscascaded to form a two-stage amplifier along with matching networks, resulting in a reasonable value ofreturn loss for sustaining device operation in low to mid-5G ranges. Two GaN HEMT’s are used in these investigations for PA design, and being modeled using theNitronex/Macom-NPT series [6] and Triquint/Qorvo-TGF series [7] High Frequency (HF) transistor S-parameters. To model the device, the two port S-parameters of NPT series transistor are
various institutions andcompanies. 182 OUTLINE1. WHY INDUSTRIAL TRAINING2. WHAT IS THE l~~C? - FOUNDING INSTITUTIONS - OBJECTIVES &/JCTIVITIES - STRUCTURE3. INDUSTRIAL TRAINING AT IMC - IDP - TAP - MAP - GAP 4. THE IDP STRUCTURE 5. VERTICAL & HORIZONTAL IDP COURSE OFFERING 5. PARTICIPATING COMPANIES 7. TAP CouRSE OFFERING g. MAP COURSE OFFERING g. GAP10. PROGRAM UPDATING11. UNIVESITY TEACHING vs. INDUSTRIAL TRAINING 183 1- WHY INDUSTRIAL TRAINING?PROBLEM • TREND 1960's - THE DECADE OF ELECTRONICS 1970's - THE DECADE OF (MICRO
Numerical Methods in the ChEn curriculum: One Program s Evolution over 30 Years (Extended Abstract) Alon McCormick, from discussions with Prodromos Daoutidis, Jeff Derby, Kevin Dorfman, Yiannis Kaznessis, and Satish Kumar Department of Chemical Engineering and Materials Science University of Minnesota, Minneapolis MN 554551980 s First ChEn course in the curriculum is Numerical Methods Ted Davis introduced required ChEn Numerical Methods course in the Sophomore year (following Freshman Fortran prerequisite) a e f f da a c e our ChEn
many seconds) does it become possible to determine if a student will struggle. Asimple neural network is proposed which is used to jointly classify body language and predicttask performance. By modeling the input as both instances and sequences, a peak F Score of0.459 was obtained, after observing a student for just two seconds. Finally, an unsupervisedmethod yielded a model which could determine if a student would struggle after just 1 secondwith 59.9% accuracy.1 IntroductionIn this work, the role of machine learning for planning student intervention is investigated.Specifically, t his w ork a sks t wo q uestions: ( i) C an a s tudent’s s truggles b e p redicted basedon body language? (ii) How soon can these struggles be predicted
Survey 0% NASA DOD S&T-10% NSF-20% DOE Science USDA R&D DHS S&T NIH NIST-30% NOAA Research-40% EPA S&
were 46 juniors surveyed the first year. Page 12.549.3There were 38 seniors and 48 juniors surveyed the second year.Assessment ResultsThe following table shows a summary of the assessment results. There are many ways that thedata and numbers could be analyzed and presented. The authors have chosen a weightedresponse based on assigned weights for each response. For reference, the table shows thepercentage response for each administration of the quiz. Percentage Response Weighted Response Question Response Response Jr.'s Jr.'s Sr.'s Jr.'s Jr.'s Sr.'s No. Choice Weight FA06 FA05 FA06 FA06
* where: − A1(T − T *) ηo = D1 exp A2 + (T − T *) Page 12.1279.5where: η is the viscosity (Pa.s), γ is the shear rate (1/s), T is the temperature (K), T* is D2+D3.P(K), P is the pressure (Pa), A2 is A2*+D3.P (K), while n, τ*, D1, D2, D3, A1, and A2* areregression coefficients based upon empirical data. For the base polypropylene used in this study,the values of these coefficients were, respectively, 0.2751 (-), 24200 (Pa.s), 4.66x1012 (Pa.s),263.15 (K), 0 (K/Pa), 26.12 (-), and 51.6 (K).Using
more on presumed difficulty with high-level concepts and specificapplication functionality. Further analysis will be presented at the conclusion of the springsemester once additional data has been collected and analyzed.AcknowledgementsT his material is based upon work supported by the National Science Foundation (NSF) underGrant No 1839357, 1839270, 1839259. Any opinions, findings, and conclusions orrecommendations expressed in this material are those of the author(s) and do not necessarilyreflect the views of the NSF.References[1] EDISON: Building the data science profession; Edison Project.[2] S. Freeman, S. L. Eddy, M. McDonough, M. K. Smith, N. Okoroafor, H. Jordt, and M. P. Wenderoth, Active learning increases student
into engineering education inthe early 1990’s and has since been a staple in introductory courses. Although many studies havebeen conducted in relation to product dissection, research has not been systematic, leaving us toquestion how variations in product dissection impact learning, creativity, or both for studentswhen used in the classroom. To fill this gap, our research group has conducted numerous studiesover the last four years in order to systematically investigate variations in deployment of productdissection in an engineering classroom. Using the findings from these studies, we havedeveloped a virtual product dissection module and deployed it in an introductory engineeringcourse. We provide recommendations for the use of product
Commerce is worried about whether we’re producing enoughSTEM graduates from our colleges and universities.” American companies are quite Page 23.506.2concerned about impending shortages of workers to fill science, technology, engineering 1 and mathematics jobs in the future. Shortages of workers trained in these fields couldlogically impede the growth of technology, lower competitiveness with otherindustrialized nations, and thereby exacerbate the decline of the U. S. economy.Likely, all engineering educators who are at all interested in policy matters have read thatChina and India are producing from 5 to 10 times
and written publications. So, I’m a big supporter of S-L, as an active learning method. The service initiative, and the service component is very powerful as long as we have good projects; and they can be well integrated into the courses.”To Increase Student Motivation to Learn: 95% of the faculty members expressed their interestin service-learning primarily because they viewed it as a way to motivate students to learn. Intheir view, students become more motivated to learn and to develop technical skills when thelearning goes beyond the classroom. Therefore, service-learning was viewed as a value-addedteaching strategy to enhance student learning of engineering content. As such, they weremotivated to use service-learning
! ! ! a uf! c t! re U! ! !! ! se & R! !t!! ! ! !e! !! e ir em n t T!r! ! !! e! !! eat m! nt A! ! ! !! i!!!! ! ! c q u is t ion P! ! ! ! ! s!! ! ! roc es! ing &!A! ! e! !b
humanistic approach to engineering education, it is a suitable frameworkto evaluate the impact of sociotechnical engineering courses (i.e., a humanistic approach toengineering education) on students’ attitudes toward and perceptions of engineering.Furthermore, this framework explicitly describes and explains the possible connections betweenstudents’ attitudes toward and perceptions of engineering, making it appropriate for a studyinterested in exploring these relationships. The framework has been used to guide how weconceptualize sociotechnical engineering. The instrument used for this study included items andconstructs that align with all three dimensions of Fila et al.’s [1] framework.MethodsSurvey responses collected from undergraduate
. Pembridge Embry-Riddle Aeronautical UniveristyRadu F. Babiceanu (Professor)Erin Elizabeth Bowen (A. Dale Thompson Professor of Leadership) © American Society for Engineering Education, 2022 Powered by www.slayte.com ASEE ANNUAL CONFERENCE & EXPOSITION COPYRIGHT TRANSFER FORMTitle of Paper: ________________________________________________________________________Author(s): ______ _____________________________________________________________________Publication: ASEE Annual Conference Proceedings Session #: ___________ PART AThe
0.63 3.34 0.60 0.472 Interest 3.68 0.99 3.87 0.92 0.0003 3.75 0.96 3.93 0.93 0.011 Open 4.54 0.47 4.48 0.61 0.002 4.51 0.53 4.52 0.52 0.743 MindednessDuring the first year curriculum, Cohort 1's population showed significant increases in four outof the six sub-constructs, less Interest and Open Mindedness. However, Cohort 2's populationshowed significant increases in only Interest and Open Mindedness, hinting at a disconnectbetween the two cohorts in their first year of their program. Previous studies have indicated theimportance of determining student perceptions of projects and teaching styles to determinenecessary changes to ensure that students are